Paper Info
Title
Distance-Guided GA-Based Approach to Distributed Data-Intensive Web Service Composition.
Abstract
Distributed computing which uses Web services as fundamental elements, enables high-speed development of software applications through composing many interoperating, distributed, re-usable, and autonomous services. As a fundamental challenge for service developers, service composition must fulfil functional requirements and optimise Quality of Service (QoS) attributes, simultaneously. On the other hand, huge amounts of data have been created by advances in technologies, which may be exchanged between services. Data-intensive Web services are of great interest to implement data-intensive processes. However, current approaches to Web service composition have omitted either the effect of data, or the distribution of services. Evolutionary Computing (EC) techniques allow for the creation of compositions that meet all the above factors. In this paper, we will develop Genetic Algorithm (GA)-based approach for solving the problem of distributed data-intensive Web service composition (DWSC). In particular, we will introduce two new heuristics, i.e. Longest Common Subsequence(LCS) distance of services, in designing crossover operators. Additionally, a new local search technique incorporating distance of services will be proposed.
Year
Venue
DocType
2019
arXiv: Artificial Intelligence
Journal
Volume
Citations 
PageRank 
abs/1901.05564
0
0.34
References 
Authors
14
3
Name
Order
Citations
PageRank
Soheila Sadeghiram100.34
Hui Ma212823.06
Gang Chen34816.42